IDEAS home Printed from https://ideas.repec.org/a/rsg/littra/2025-013.html

Development and Forecast of Unemployment in the Czech Republic

Author

Listed:
  • Tereza Kalinová
  • Vilém KovaÄ

Abstract

Unemployment is one of the key indicators of the state of the economy and labor market stability, and its development is sensitive to economic cycles and extraordinary economic shocks. The aim of this study was to evaluate the development of unemployment in the Czech Republic over the last ten years, identify the key factors influencing its dynamics, and propose a predictive model for estimating future developments. To achieve this goal, time series analysis, multivariate regression analysis, and the ARIMA seasonal model were used. The results showed significant seasonality in unemployment and its decline to historically low levels in 2017 2019. The impact of the COVID-19 pandemic was only a temporary disruption of the long-term trend, followed by a stabilization of the unemployment rate. The number of registered job seekers and the number of job vacancies had a significant impact on the development of unemployment. The prediction indicated a slight increase in the unemployment rate in 2026 without any indication of a significant structural break. The paper provides a comprehensive view of unemployment trends and, with the proposed model, offers a tool for further research and decision-making in the labor market. However, the scope of available data is a limitation.

Suggested Citation

  • Tereza Kalinová & Vilém KovaÄ, 2025. "Development and Forecast of Unemployment in the Czech Republic," Littera Scripta, VSTE, vol. 18(2), pages 96-114, December.
    • Handle: RePEc:rsg:littra:2025-013
    DOI: 10.36708/LS.2025.I02.006
    as

    Download full text from publisher

    File URL: https://littera-scripta.com/articles/development-and-forecast-of-unemployment-in-the-czech-republic-4c4bac4d
    Download Restriction: no
    File URL: https://littera-scripta.com/api/v1/public/files/94f110f1-ece3-4b5a-a9f8-ed13dbd6474c
    Download Restriction: no
    File URL: https://libkey.io/10.36708/LS.2025.I02.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Muneeb Ahmad & Yousaf Ali Khan & Chonghui Jiang & Syed Jawad Haider Kazmi & Syed Zaheer Abbas, 2023. "The impact of COVID‐19 on unemployment rate: An intelligent based unemployment rate prediction in selected countries of Europe," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 528-543, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:hal:journl:hal-04675599 is not listed on IDEAS
    2. Iwona Kaczmarek & Adam Iwaniak & Grzegorz Chrobak & Jan K. Kazak, 2025. "Integrating media sentiment with traditional economic indicators: a study on PMI, CCI, and employment during COVID-19 period in Poland," Journal of Computational Social Science, Springer, vol. 8(2), pages 1-23, May.
    3. Peterson Ozili & Olajide Oladipo, 2024. "Impact of credit expansion and contraction on unemployment," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 52(2), pages 205-219, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rsg:littra:2025-013. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Robin Kunju Mol Raj (email available below). General contact details of provider: https://littera-scripta.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.